Top 5 YouTube Channels

YouTube is a great resource to learn new development topics. It is one of my go to places if I want to learn a new topic or even to get into a specific area. However, there are a few channels that I make sure and check out if there are new videos.

Traversy Media

One of my favorite channels, Brad really has some great content. Mostly going over web technologies he definitely goes over the big three frameworks - React, Angular, and Vue. However, he also goes over some pure CSS, HTML, and JavaScript in some of his videos. He also has videos that go over career and personal development issues that I find very helpful.

Fireship.io

This channel used to be called Angular Fire and by the name you may guess what he covers - Angular and Firebase. However, he's branched out quite a bit into some other videos such as Flutter for mobile applications. He has some of the best RxJS videos that I've found very helpful.

Academind

Maximilian Schwarzmüller is one of my favorite instructors for web based technologies. He has courses in all of the current popular frameworks - Angular, React, and Vue. He also has courses in some other technologies which may be useful to learn, such as Flutter and React Native for mobile applications and AWS for serverless applications.

Corey Schafer

Corey's channel is probably the most popular in terms of Python content. He's got so many videos that whatever you need to do in Python he already has a video about it. Another great thing about this channel is that he also goes into other developer tools, such as bash and dot files which I just started watching, as well as git.

Data School

The Data School channel is the best if you want to learn data wrangling and data cleaning with pandas or machine learning with scikit-learn. You can tell he has a deep knowledge with both of these libraries.

Completing the Microsoft Professional Program for Data Science

Microsoft has two data related certifications in their Microsoft Professional Program - one for Data Science and another for Big Data. I recently completed the one for data science and want to share my experience to others interested in doing the same.

Program Details

The data science program consists of 10 courses, with one being an orientation and the last being a final capstone project. In order to get credit you do need to receive a passing grade (70% for all courses other than the capstone in which you need 76%), and to purchase a verified certificate. The certificates cost $99 so the whole course will cost you $990. A good chunk of change if your employer won't reimburse you on it, so I would definitely check that first before committing the time.

The main course materials cover the following:

  • Statistics
  • Coding in R or Python
  • Machine Learning
  • Visualizing Data

The courses all differ in how they do the grades, but usually they have either a lab or quiz after each section and a final exam at the end of the course. The questions usually allow you two chances to get the correct answer, but some may only offer one.

My Experience

Most of the courses are easy as long as you pay attention to the lectures and actually do the labs. The instructors were all knowledgable and presented the materials well, however, I think there was an issue with the materials involving the math and statistics.

To go over the math portions to try to explain a concept, they showed slides of the formulas and just talked about what the formulas mean...and that's basically it. I don't think this was needed at all since the concepts were explained much better once they were put as demos. Just going over formulas isn't the best way to teach any kind of math. Showing the applications of it, though, is. Then if you need to go back to the formula you can while relating it to the application.

Speaking of which, the statistics course was the hardest for me. I barely made a passing grade. The course structure was slightly different

Tips

A couple of things that may be useful to you if you do decide to take this course:

  • Audit the course first. Then, once you know you've gotten a passing grade, purchase the certificate. There's nothing worse than paying for something and come to find out you barely missed the passing grade and you've payed $99 for nothing.
  • The statistics course was harder than expected. Not only do they only allow one choice to choose an answer instead of the usual two, the questions don't make it clear what part of the lectures it comes from. I would definitely go back over the lectures after reading each question. They will mostly come from the Excel portions of the lectures.

Conclusion

Would I take this course again if I needed to? I probably would, but I love to learn. I did learn a lot of things, such as tuning models in Azure Machine Learning, how awesome PowerBI is and all the things you can do with it, and time series analysis concepts.

In the end, you get a certificate that you can share on LinkedIn or to your boss. However, keep in mind that there's still tons more to learn and projects to work on to futher solidify the concepts from this course.

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Book Review: Becoming a More Effective Developer

A lot of programming books teach you about a new framework, language, or computer science theory, but very few teach you how to actually be effective at your day job. The book, The Effective Engineer is a great one to learn all the ways in which you can be the best developer you can be.

 
 

This book goes through three main points:

  • Developing the right mindset
  • Executing effectively
  • Building long term value

Each of these has some really good and actionable insights on how you can become better as a programmer.

Developing the right mindset

As Carol Dweck mentions in her book Mindset, the most successful people have a certain mindset in terms of how they view their learning. They believe that your brain can be changed and you can learn anything once you put in the work. That's definitely true for programmers.

Continuous Learning

A large part of being a software developer is that you are continuously learning new things. Whether new frameworks, languages, or software theory, there is no shortage of things to learn.

A majority of the time this learning comes from actual work on the job. No longer being able to learn on the job is a reason a lot of developers change jobs, so it's definitely cared about. Sometimes, though, that learning may need to be supplemented outside of the job. This is where you hear some developers doing projects and learning during nights and weekends.

The book goes through a few ways developers can actually do this learning, such as reading code from developers who are more experienced and to have them review your own code.

Prioritize

One of my favorite authors, Tim Ferriss often talks about being efficient vs. being effective to help boost productivity:

Focus on doing the right things (efficiency) vs doing things well (being efficient).

Doing things to be efficient may include items such as replying to emails, updating status reports more than they need to be, and other tasks that make it seem like you're busy but doesn't actually contribute much to the project you're working on.

That's where prioritization comes in. Once you take some time each day or week to prioritize what needs to be done, you'll have a clear way to move forward with the actual project.

This is similar to Getting Things Done in that you define clear tasks and prioritize the ones that need to be done. I would also argue to break up bigger tasks into much smaller ones.

Executing effectively

Now that we have the right mindset for our productivity, we also need to know how to execute them. A few things from the book stand out in what I believe will help the most.

Master Your Environment

Do you use Visual Studio for all of our development? Then knowing as much as you can about it can save you so much time in terms of keyboard shortcuts or knowing when to move to the command line for certain tasks. Speaking of the command line, knowing PowerShell or bash can save you a ton of time as there are snippets and commands that can do a lot that you may not even know of.

Improve Your Estimation Skills

All too often you, as a developer, will get asked by your boss or a manager how long a certain task will take. How often have you said, "I don't know?" Improving your estimation skills is an easy way to be thought of as a senior programmer.

The main way to improve this is to just keep track of your tasks. Once you are asked to estimate you can refer back to your tasks and get an idea of how long it took you to do something similar.

There's also the book Software Estimation that can give a lot more details in improving your estimation details.

Building long term value

To be the best programmer you can be is to build long term value for your company and your clients. The book offers some great ways in order to help you build that long term value.

Balance Quality with Practicality

How often have you come across this scenario: you implement a new feature and the deadline is very close, however your boss wants you to go ahead and get it in to start testing. You mention how many more tests you need to write, yet your boss says to not worry about that and just check it in. Often referred to as technical debt, us programmers can perfectionists in that we want our code to be perfect before we send out for all to work on and see.

Having this type of balance on having your work be perfect vs. being practical in your work can be beneficial in terms of providing value to your company or clients.

Invest in Your Team

I think the biggest thing you can do for long term value is investing in the team. This can be done in many ways, such as the following:

  • Providing a nice way to onboard new team members: Having a good onboarding solution will make new team members so much more productive and have them committing code within their first week on the job. This leads to higher morale overall across the team.
  • Collaborating on all aspects of the code: This includes having efficient code reviews on all pull requests, and team members not afraid to volunteer for certain bug fixes or features.
  • Building a great culture: This can be a hard one to accomplish, but if done correctly this will build higher morale with the team which will reflect team members making sure they give everything their best.

Of course there are other ways to help invest in your team, but these are some of the ways that can have the most impact.


This book is definitely worth reading for a lot of ideas on how you can easily improve your effectiveness as a programmer. For even more you can checkout the book's blog.

Learning Math for Programming

When I went to college I had to take math. My degree is actually in Math and Computer Science. Why the math part, you ask? Well, the folks at the school figured that the math will help with a lot of the logic that comes with programming.

Of course, there's also that age old question when you first start learning programming...is there a lot of math involved? The answer is it depends. If you're planning to get a doctorate and do a lot of research, then you'll most likely use a lot of it. However, if you're just working for a company, then chances are you won't need hardly any math*. If you're learning data science then some math is essential in order to gain insights from data or to understand machine learning algorithms.

In this post, we'll go over the most common types of math you may want to be familiar with to get the most out of your programming, and where you can start learning these concepts.

Discrete Math

Discrete math is used quite a bit in programming. Whether it's understanding the theory of how integers work in programming languages or using boolean logic, you've probably come across it before.

Where to Learn

Coursera comes to the rescue here as there may not be too much around discrete math.

Algebra

Yep, even plain old algebra you probably didn't like in high school can be helpful. I actually have an example of this: back when I was doing tax software I needed to use some basic algebra to create a function. Of course, tax software relies heavier on math than most other software, so it's not unusual. Knowing that bit of algebra that I needed, though, really helped when creating the function and I may have had to spend a good bit of time Googling for some help.

Where to Learn

Kahn Academy is well known for their math courses and they definitely have a good algebra one.

For a book, Practical Algebra looks to be a good one to brush back up on your algebra.

Statistics

Statistics is needed for data scientists, not only to help get insights from your data but to also make sure variables that seem correlated to each other actually are statistically significat rather than not. That's not the easiest to do even if you plot your data. Statistics will give you a big advantage in understanding your data and how it can answer any questions you can throw at your data.

Need to see if an A/B test has a significant difference? Then statistical hypothesis testing can be of a great help.

Where to Learn

Coursera has a great intro to data course that has really helped me out in learning some of the basics of statistics. The book they recommend, too, is actually really good.

As for books, I recommend a couple to start with. Practical Statistics is a great introduction. If you want to focus more on the data science side of statistics then Practical Statistics for Data Scientists is a great one to get.

If you want to get a bit advanced, then I definitely recommend Introduction to Statistical Learning. This is mainly for getting deep in the machine learning algorithms, but still is an interesting read. You can also read it for free online instead of getting a physical copy. There's an even more advanced version of this too with The Elements of Statistical Learning, which is also available for free online.

Linear Algebra

Linear algebra is a bit of a niche in programming. The only place I've really seen it used is for machine learning algorithms. Linear algebra, is mainly matrix manipulation.

Where to Learn

Khan Academy has some linear algebra courses that you can take. This is probably the most complete of them I've seen around.

For a book, mostly what you'll see are text books. That's not all bad, but sometimes a more general book is helpful. In that case there's Linear Algebra for Dummies.


While math isn't necessary for programming, I believe it can certainly help with the logic like my university thought. Learning the extra math also made me appreciate it more for what all math can teach us about the world. Also, don't think you're not good at math. This old post from Steve Yegge explains more about the way math is taught in schools and what we can do about it as programmers. You're not bad at math, you just need a better way to learn it.

* Though, depending on the company you work for you may need it. For example, working for a financial institution may involve some knowledge of math.

Best Pluralsight Videos to Help Your Career

Pluralsight has certainly grown over the years. I remember when it first started and it had only courses that were just .NET based and maybe a few others within the Microsoft stack. Now they cover, not only a wide range of development topics, but a big range of creative, admin, and business topics. With that, several videos about how you can get better at your career and as a developer have come up. Here are my favorite courses that I feel give great, actionable advice on how to get better.

Becoming an Outlier: Reprogramming the Developer Mind by Cory House

This is a great course that is very actionable. Cory goes into several things that you can use right after you watch it on how to make yourself an outlier, or an above average developer. Of course, it's going to be some work, but all that work will pay off. I tend to refer to this course when I need a bit of extra motivation to be an outlier.

Play by Play: Crafting a Brand for Growth and Prosperity

The Play by Play is an interesting concept. Usually it's where you follow a developer as they are making an application or doing something similar to their day-to-day programming and they talk through what they're doing and what they're thinking. In this case, it's more of an informal discussion where Troy Hunt and Lars Klint discuss how they update their brand and image to rise above average and help get themselves noticed. They talk about their experiences so you can learn from them and incorporate them into your own career.

Learning To Program - Being A Better Programmer

Programming is mostly a job of learning. Developers are constatly learning new technologies and frameworks. In this course, Iris Classon and Scott Allen help you learn how to learn in terms of programming. Probably the best section is the "Learning Plan" section. You can't really learn that much if you don't have a plan, from going through tutorials, practicing, and retaining what you've done.

Get Involved!

One of the best things to do while being a programmer is to, well, get involved. There are a ton of ways to get invovled and this course details those ways. From the usual getting into open source projects to participating in local user groups. Why get involved? Getting involved will help your personal brand, which the first two courses go into much deeper. Getting involved gets you known around the community. Getting involved with the local community lets you meet people easier and, who knows, you could be talking with a member of the community you meet and come up with the next innovation in programming.

The Future of Technology Careers

Programming is a very dyanmic career. The reason developers are always learning is that new technologies and frameworks are always coming out for us to learn. One of those will become very popular and you would need to get up-to-speed quite quickly to meet the needs of a client or employer. This course was done in 2015 and predicts quite a few things that are still emerging, such as virtual reality, big data or data science, and artificial intelligence.

UPDATE: Dan Appleman just released an awesome new course on keeping up with technology. It's done very well and goes well with the other courses in this post.


PluralSight definitely offers a lot and new courses are added each day. While I wish they offered more in terms of exercises or projects, they are top notch in terms of video tutorials. The ones I highlighted in this post are great to help you use the other more techical courses that they offer. I hope you get as much out of these courses as much as I have!